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Ideally positioned at the end of <body>. (Available only from version 3.1 and more) By default, FuckAdBlock is instantiated automatically. To block this automatic instantiation, simply create a variable "fuckAdBlock" with a value (null, false, ...) before importing the script.

Arachni is a feature-full, modular, high-performance Ruby framework aimed towards helping penetration testers and administrators evaluate the security of web applications. It is smart, it trains itself by monitoring and learning from the web application's behavior during the scan process and is able to perform meta-analysis using a number of factors in order to correctly assess the trustworthiness of results and intelligently identify (or avoid) false-positives.

Extract prominent colors from an image. Vibrant.js is a javascript port of the awesome Palette class in the Android support library. Please file issues over on the node-vibrant repo, this repo is kept solely for historical reasons, but ongoing development will happen over there. Despite node-vibrant's name, it works with both node and the browser (with and without UMD support). It is highly recommended you use that project over this one.

Simple Node.js API for robust face detection and face recognition. This a Node.js wrapper library for the face detection and face recognition tools implemented in dlib. Installing the package will build dlib for you and download the models. Note, this might take some time.

By its nature, JavaScript lacks the performance to implement Computer Vision tasks efficiently. Therefore this package brings the performance of the native OpenCV library to your Node.js application. This project targets OpenCV 3 and provides an asynchronous as well as an synchronous API. The ultimate goal of this project is to provide a comprehensive collection of Node.js bindings to the API of OpenCV and the OpenCV-contrib modules. An overview of available bindings can be found in the API Documentation. Furthermore, contribution is highly appreciated. If you want to get involved you can have a look at the contribution guide.

SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.

A python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. Built with simplicity in mind, ImageAI supports a list of state-of-the-art Machine Learning algorithms for image prediction, custom image prediction, object detection, video detection, video object tracking and image predictions trainings. ImageAI currently supports image prediction and training using 4 different Machine Learning algorithms trained on the ImageNet-1000 dataset. ImageAI also supports object detection, video detection and object tracking using RetinaNet, YOLOv3 and TinyYOLOv3 trained on COCO dataset. Eventually, ImageAI will provide support for a wider and more specialized aspects of Computer Vision including and not limited to image recognition in special environments and special fields.

Commix (short for [comm]and [i]njection e[x]ploiter) is an automated tool written by Anastasios Stasinopoulos (@ancst) that can be used from web developers, penetration testers or even security researchers in order to test web-based applications with the view to find bugs, errors or vulnerabilities related to command injection attacks. By using this tool, it is very easy to find and exploit a command injection vulnerability in a certain vulnerable parameter or HTTP header. Usage of commix for attacking targets without prior mutual consent is illegal. It is the end user's responsibility to obey all applicable local, state and federal laws. Developers assume no liability and are not responsible for any misuse or damage caused by this program.

OpenBR is a framework for investigating new modalities, improving existing algorithms, interfacing with commercial systems, measuring recognition performance, and deploying automated biometric systems. Off-the-shelf algorithms are also available for specific modalities including Face Recognition, Age Estimation, and Gender Estimation.

❗️ NOTE: THIS PLUGIN IS NO LONGER MAINTAINED. If you encounter a bug then you're probably on your own. Try Bowser as an alternative. Note: Detect.js is a JavaScript library to detect platforms, versions, manufacturers and types based on the navigator.userAgent string. This code is based on, and modified from, the original work of Tobie Langel's UA-Parser: https://github.com/tobie/ua-parser. UA-Parser is subsequently a port of BrowserScope's user agent string parser.